Augment data with predictions
augment() will add column(s) for predictions to the given data.
## S3 method for class 'model_fit' augment(x, new_data, ...)
For regression models, a .pred column is added. If x was created using
fit() and new_data contains the outcome column, a .resid column is
also added.
For classification models, the results include a column called .pred_class
as well as class probability columns named .pred_{level}.
car_trn <- mtcars[11:32,]
car_tst <- mtcars[ 1:10,]
reg_form <-
linear_reg() %>%
set_engine("lm") %>%
fit(mpg ~ ., data = car_trn)
reg_xy <-
linear_reg() %>%
set_engine("lm") %>%
fit_xy(car_trn[, -1], car_trn$mpg)
augment(reg_form, car_tst)
augment(reg_form, car_tst[, -1])
augment(reg_xy, car_tst)
augment(reg_xy, car_tst[, -1])
# ------------------------------------------------------------------------------
data(two_class_dat, package = "modeldata")
cls_trn <- two_class_dat[-(1:10), ]
cls_tst <- two_class_dat[ 1:10 , ]
cls_form <-
logistic_reg() %>%
set_engine("glm") %>%
fit(Class ~ ., data = cls_trn)
cls_xy <-
logistic_reg() %>%
set_engine("glm") %>%
fit_xy(cls_trn[, -3],
cls_trn$Class)
augment(cls_form, cls_tst)
augment(cls_form, cls_tst[, -3])
augment(cls_xy, cls_tst)
augment(cls_xy, cls_tst[, -3])Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.